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Idealization and the Laws of NatureThe Algorithmic Theory of Laws

Idealization and the Laws of Nature: The Algorithmic Theory of Laws [Chapter 4 brings together the insights of the first three chapters, and argues that the best way to understand ideal laws is to think of them as rules or algorithms for compressing empirical data. Idealization is explained as a form of lossy compression. Lossy compression is tolerated in scientific theories because of predictive redundancy in our theories. Idealizations in scientific theories and their application are accounted for as compression artefacts left over from the lossy compression. A number of possible objections to this explanation are considered and responses given.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Idealization and the Laws of NatureThe Algorithmic Theory of Laws

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Publisher
Springer International Publishing
Copyright
© The Author(s), under exclusive license to Springer Nature Switzerland AG, part of Springer Nature 2018
ISBN
978-3-319-99563-2
Pages
79 –109
DOI
10.1007/978-3-319-99564-9_4
Publisher site
See Chapter on Publisher Site

Abstract

[Chapter 4 brings together the insights of the first three chapters, and argues that the best way to understand ideal laws is to think of them as rules or algorithms for compressing empirical data. Idealization is explained as a form of lossy compression. Lossy compression is tolerated in scientific theories because of predictive redundancy in our theories. Idealizations in scientific theories and their application are accounted for as compression artefacts left over from the lossy compression. A number of possible objections to this explanation are considered and responses given.]

Published: Aug 29, 2018

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